Micah P. Dombrowski / Jun 10 2018

Python Template

This article can act as a starting point for any basic Python article. It has cells to accomplish some basic setup and programming tasks, as well as a few more complex ones. Just Remix and go!

For explanations of what's going on, see this article on Bash setup and this one on Python setup and coding.

1.
System Setup

apt-get update >> /dev/null
apt-get install -y fortune cowsay make g++
/usr/games/fortune | /usr/games/cowsay
15.8s
install system packages
Setup (Bash in Python)Python Default↩













































































































































































































































































pwd
ls -al
mkdir -p ~/.keras
echo '{
    "epsilon": 1e-07, 
    "image_data_format": "channels_last", 
    "backend": "cntk", 
    "floatx": "float32" 
}' > ~/.keras/keras.json
0.7s
dir & file creation
Setup (Bash in Python)Python Default↩





























# curl -O https://nextjournal.com/images/logo.svg
wget https://nextjournal.com/images/logo.svg

cp ~/.keras/keras.json /results/
cp logo.svg /results/
0.6s
file download & manipulation
Setup (Bash in Python)Python Default↩
keras.json

2.
Installing Python Packages

conda install -y seaborn sympy
pip install xgboost
208.0s
install python packages
Setup (Bash in Python)Python Default↩

Remember to Review & Save the Setup environment before continuing!

3.
Data intake

cubic.csv
import pandas as pd

data = pd.read_csv(cubic.csv↩)
0.5s
read data
PythonSetup↩
with open(keras.jsonfile download &  manipulation↩, "r") as f:
  str = f.read()

str
0.7s
read text
PythonSetup↩
print(str)
0.8s
print text
PythonSetup↩

4.
Calculations

from sympy import primerange

[i for i in primerange(1,1000)]
0.6s
use module function
PythonSetup↩
split_data = [float(x[0])*(-1)**(i+1) for (i,x) in enumerate(data.values)]

# Return data for use by Javascript cell
split_data
0.3s
modify file data
PythonSetup↩

4.1.
Plotting

import matplotlib.pyplot as plt

plt.figure()
plt.plot(data)
plt.title("Cubic Function")
plt.ylabel("f(x)")
plt.xlabel("x")
plt.savefig("/results/blah.png")
0.3s
pyplot plot
PythonSetup↩
import plotly.plotly as plt
from plotly.graph_objs import Scatter,Layout,Figure

Figure(
  data = [
    Scatter(y=data.values[:,0])
  ],
  layout = Layout(
    title = "Cubic Function",
    yaxis = dict(title="f(x)"),
    xaxis = dict(title="x")
  )
)
0.6s
plotly plot
PythonSetup↩
var data = nilmodify file data↩

plottypes = ['lines','markers']

var traces = plottypes.map(function(ptype) {
  return { type: 'scatter', mode: ptype,
    name: ptype,
    x: [...Array(401).keys()],
    y: data
  }
})

var layout = { title: 'Split Cubic Function',
  xaxis: { title: 'Year' },
  yaxis: { title: 'Temperature [C]' }
}

Nextjournal.plot(traces, layout)
calm-resonance
Javascript↩